A comparative study of United States and China exchange rate behavior: A co integration analysis
Bibliographic record
Abstract
Exchange rates always affect the prices of the imports and export of products and services in which countries are trading with other parts of the world.Therefore, exchange rate calculation is one of the essential issues for making appropriate policies.This research investigates the determinants of trade, i.e. import, export, industrial growth, consumption level and oil prices fluctuation, which bring changes in exchange rate and their influence eventually on balance of payments.Data of defined variables was collected on yearly basis for China and USA for thirty one years.By applying cointegration, it is estimated that there existed a long run relationship in both countries.USA and China had significant and correct signs on the short run dynamic and some of the factors did not.Exchange rate did not granger cause balance of payment and balance of payment did not granger cause exchange rate.In conclusion, we found that determinants of balance of trade could affect the exchange rates, also, these rates had considerable effect (positive or negative) on balance of payments.In this twofold study, we found relationship of exchange rate with selected determinants of trade, and also examined their bilateral effect, and then made contrast of both countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".